#142 now when it was on the front-page mere minutes ago: I guess, TFA is way too exaggerated & seeped in avoidable animosity to warrant it.
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To my surprise, providers on OpenRouter (io/akash/chutes) are serving Qwen3.8 27B at ~ $0.4 (in) / $3 (out) / $0.25 (cache), more expensive than DeepSeek v4 Flash.
https://openrouter.ai/qwen/qwen3.8-27b / https://archive.vn/RrDGO
Once you send your benchmark to "cloud", I don't think you can rely on it being secret/private any longer.
Per Artificial Analysis benchmarks, Meta's Muse Glimmer 30b (open weight) holds its own (for agentic code workloads) against models 5x to 10x its size, too.
We will get to a point where prosumer laptops that etch SoTA LLMs in removable silicon will be as expensive as cars.
Go is similar to popular languages like C, JS/TS, & Python. And so, easy to get started.
> highly value a type system that catches errors
Probably these folks already use even less popular ML-style languages like OCaml & Haskell; or (comparatively) obscure ones like Agda, Idris, & rocq/Coq.
Sarcasm or irony?
For instance, this "marketing" claim that it'll take 24y to break even if a user only uses 100m tokens/day (~$1.14 in DeepSeek v4 Flash usage) ignores the fact that OpenCode Go has 5h & weekly throttles. Besides, folks who self-host models usually run automated jobs [0]. I think the GPU setup could possibly serve 10+ "users" concurrently, bringing down the break even by 22y (10x).
[0] For comparision, we routinely do 200m to 500m tokens ($2 to $5) on merely 3 to 8 automated code reviews per day with DeepSeek v4 Flash on max.
Surprising that Meta don't host this model, even as rate-limited free-tier.
> open weight version of Muse Spark 1.2
Wait. Is this "version" different from what Meta serves?
Open weights*
I don't think outside of the Big 3 (Ant, OAI, GDM), given the strong competition from China, any other Lab has a chance at capturing the coding market if they aren't open weights (save for xAI whose latest Grok looks every bit good & will probably rely on Cursor for distribution instead of going open weights). There's literally no other selling point, as the capabilities have mostly converged by now among the chasing pack.
Even often so, what might be a problem for some, will be a desirable solution for others. Cue the utilitarians...
If today's top LLMs are reliable enough (without grounding) to academically learn "complex topics" from, may be I need to adjust my priors. I must say, I do find myself chatting about other topics (without the need for grounding) that I'm trying to "absorb" (not really learn), like Behavioural Psychology & Philosophy.
[0] Products like NotebookLM are built specifically for such usecases.
> working on some more commercial features, like the ability to monitor queries (e.g. for backlinks or brand mentions) and get an email when there are new results
As an inspiration (presuming you don't already know), see exa.ai who build generic solutions in similar space: https://exa.ai/docs/reference/monitors-api-guide
Careful with using OpenCode's accounting for DeepSeek v4 Pro, though: https://github.com/anomalyco/opencode/issues/39822
My read is, OpenAI is neither able to claw b2b money (away from Ant) nor are they able to stave off open weights on the other. In short, they're struggling to hold onto their distant #2 position in the coding market, and these pricing changes reflect a (desperate) change in strategy.
If you prefer subscriptions, OpenCode Go ($10/mo), Cline Pass ($10/mo), Atlas Code ($20/mo), and CommandCode ($1/mo) serve some of the best open weights with generous limits. OpenCode Go currently offers $120 for $10 on DeepSeek Flash v4 (if you're okay with data retention).
https://reddit.com/r/DeepSeek is where the fellow F5ers are at.
Every week, 1 billion people turn to ChatGPT for everything from quick questions and web searches to planning, research, advice, and complex decisions.
[0] Won't put it past OpenAI (and/or Google) to open weight larger models!
Curious: Which one?
> MiMo-V2.5-Pro to be a pretty cost-effective alternative ... I found it after spotting it on a chart of different models and it was listed as being near DeepSeek v4 Flash's price/performance levels.
MiMo v2.5 Pro is at DeepSeek v4 Pro price level (but consumes lesser tokens per task, so cheaper overall). DeepSeek v4 Flash costs ~3x lesser than the Pro variant!
Yep. Super strange. @dang?
We're also beginning to accept requests for zero data retention. Contact Meta sales to request this.
MiniMax's "token plan" ($20/mo for 1.7b tokens) is cost competitive. MiniMax M3 is equally good, if not better than DeepSeek v4, at coding: https://platform.minimax.io/subscribe/token-plan?tab=individ...
If you prefer pay-as-you-go, then Xiaomi MiMo is the only other provider with comparable models (MiMo v2.5 & Pro) that matches DeepSeek's current API rates for input/output/cache: https://mimo.mi.com/docs/price/pay-as-you-go
Meanwhile, Meta is running a 10x discount on Muse Spark 1.2 (Grok 4.5 / Sonnet 5 level model), if you opt-in to data sharing: https://dev.meta.ai/docs/getting-started/pricing-rate-limits
> I'm OK spending max $100/month on APIs, ideally with Zero data retention.
In that case, probably you'll get more out of OpenAI's coding plan, as (from what I hear routinely) the GPT 5.6 series is thrifty with token use but as smart as the Claude 5 series: https://x.com/ArtificialAnlys/status/2085083490056589784 / https://archive.vn/3VDlN